Life cycle cost approach has emerged as an effective tool to assist designers at early design stage of a product in the product development process. It is necessary to estimate accurately the cost of the product for analysis of design alternatives. In this paper, an improved Artificial Neural Network approach (ANN) is proposed which combines a Genetic Algorithm (GA) with the back propagation neural network for accuracy in cost estimates. The connection weight of neuron is represented as chromosome to optimize in layers of network. The approach for estimation of product lifecycle cost has been validated with the cost data of regular sorted cardboard product from the literature. The result shows that the proposed improved ANN outperforms the traditional ANN. © Research India Publications.